Predicting Performance in Quantitative Research at the University of the West Indies: A Case of Self Assessed Competences vs. Actual Grades Trevor Smith, January 8, 2015 1 MSBM Inaugural Conference- Business & Management 2015
Background to Problem The need for quantitative skills • Countries and their industries have embraced quantitative methods as the business and econometric tool for analyzing business problems • The decline in productivity in countries such as the United States has been associated with declining skills among students in mathematics and sciences • There has been ‘talk’ that quantitative skills are rapidly declining among students in the West and that this decline could be indicative of the struggling economies of the western world. 2
More Problems Comparative study of Social Science and Education students, from Finland and USA, Murtonen (2005) found a negative orientation towards quantitative methods among students from both countries. Students were either: • Experiencing difficulties in learning quantitative methods • Lacking appreciation for empirical work. Many university students continue to suffer from : • Statistical anxiety (an aversion the student encounters when faced with statistics) • A general inhibition to pursue quantitative research (Baloglu et al., 2011; Bradstreet, 1996; Kennett et al., 2009) 3
The Problem continues at the graduate levels Statistical anxiety is experienced by approximately 80% of graduate students ; and is found to have a debilitating effect on performance in both statistics and research methods courses (Onwuegbuzie, 2004). 70% of graduate students do not read the ‘Methods’ section when assigned quantitative articles because they find the material complex; and do not understand how methods are linked to the hypotheses being tested (Corner, 2002, p. 671). 4
The Gap Quantitative methods as well as the science of learning research in general have not been extensively studied despite the difficulties that students experience in this area (Murtonen et al., 2008). 5
Addressing The Gap • Research Questions – 1a : What are the factors that will improve students’ proficiency in quantitative research among university students? – 1b: How will these factors impact students’ self -determination of proficiency vis-à-vis proficiency determined by actual grades
Theoretical Foundation Knox’s Proficiency Theory of Adult Learning • Proficiency is the unifying concept for relating knowledge , skills and attitude to improve performance of the adult learner (Knox, 1980). • If the student has acquired the knowledge, gained the skills and displays the right attitude towards the subject matter, then he or she will perform ‘satisfactorily’, ceteris paribus 7
Theoretical Foundation Self Determination Theory • SDT focuses on the degree to which an individual’s behavior is self-motivated and self-determined(Deci & Ryan, 1980) • SDT concerns with the motivation behind the choices that people make without any external influence and interference. 8
Factors that could influence Proficiency • The review of the contemporary literature in this research has led to six separate factors that could influence proficiency in quantitative research. These are: 1. Student motivation (Breen & Lindsay, 1999) 2. Competence with statistical software (Proctor, 2002) 3. Quantitative aptitude (Schuhmann et al., 2005) 4. Aptitude for data analysis (Onwuegbuzie, 2000) 5. Understanding statistics (Corner, 2002; Murtonen, 2005) 6. Teacher’s influence (Knox, 1988) 9
Research Model and Hypotheses Student Motivation and Proficiency in Quantitative Research – It was found that students who considered proficiency in research as important to the world of work { proficiency } had a deeper approach to learning { motivation }and found it easier to learn research methods than other students (Murtonen et al., 2008). – Thus, it is proposed that: H1: Student motivation is positively associated with proficiency in quantitative research 10
Research Model and Hypotheses Competence with Statistical Software and Proficiency in Quantitative Research - Competence with statistical software was found to be a positive indicator of performance in quantitative research (Proctor, 2002). - In his study of Excel and SPSS users, Proctor (2002) found that: 1. Students randomly assigned to use Excel for statistical analysis reported higher levels of proficiency in quantitative methods than those randomly assigned to use SPSS. 2. Excel users had a better understanding of, and competence with, the software than SPSS users. Hence, it is proposed that: H2: Competence with statistical software is positively associated with proficiency in quantitative research 11
Research Model and Hypotheses Quantitative Aptitude and Proficiency in Quantitative Research – Quantitative aptitude was found to be a very important determinant of performance in economics on both pre and post course surveys (Schuhmann et al., 2005). Hence, it is proposed that: H3 : Quantitative aptitude is positively associated with proficiency in quantitative research 12
Research Model and Hypotheses Aptitude for Data Analysis and Proficiency in Quantitative Research – Aptitude for data analysis and understanding of measurements are highly correlated; Also, – Understanding of measurement will deepen the student’s capacity and improve his/her performance in quantitative research; thus implying a positive relationship between aptitude for data analysis and proficiency in quantitative research (Corner, 2002). Hence, it is proposed that: H4: Aptitude for data analysis is positively associated with proficiency in quantitative research 13
Research Model and Hypotheses Understanding Statistics, Teacher’s Influence & Proficiency in Quantitative Research – Bad teaching is negatively associated with competence in quantitative research as the large majority of students are already saddle with statistical anxiety and negative attitudes to research (Corner, 2002; Murtonen, 2005). – understanding of statistics is a well establish precursor to performance in quantitative research (Bell, 2003). Taken together, It is therefore proposed that: H5: Understanding statistics is positively associated with proficiency in quantitative research H6: Teacher’s influence is positively associated with proficiency in quantitative research 14
Operationalizing Knox’s Theory ATTITUDE Student Motivation Understanding Proficiency in KNOWLEDGE statistics Quantitative Research PERFORMANCE Teacher’s Influence SKILLS Quantitative Aptitude Competence with Aptitude for statistical software Data Analysis 15
Research Model and Hypotheses Student Motivation H 1 (+) Competence with statistical software H 3 (+) Quantitative Aptitude Proficiency in Quantitative H 4 (+) Research Aptitude for Data H 5 (+) Analysis H 6 (+) Self-determination (LIKERT) Understanding vs. actual grades (GPA) Statistics Teacher’s Influence 16
Methodology Sample Items 5 point Likert scales (strongly disagree …. strongly agree) Understanding Statistics (8 items); Alpha = .895 • ‘I have a good understanding of statistical tests’, ‘ I have a good understanding of p values’ and ‘ I have a good understanding of the concept of confidence intervals ’ Competence with Statistical Software (2 items); Alpha = .847 • ‘I am hands - on with at least one statistical software (e.g. SPSS, EXCEL, SAS, MINITAB)’ ‘ I am able to effectively apply the software to research hypotheses ’ • Student Motivation with Quantitative Research (4 items); Alpha = .610 ‘I am motivated by quantitative research’, ‘I believe quantitative research is very important to my future career’, ‘ ‘I do not enjoy quantitative research ’ Quantitative Aptitude (3 items); Alpha = .736 • ‘I would say I’m strong at quantitative courses’ ‘ I tend to be a bit uneasy with number crunching ’ 17
Methodology cont’d Sample Items 5 point Likert scales (strongly disagree …. strongly agree) • Aptitude for Data Analysis (4 items); Alpha = .853. ‘I am comfortable with quantitative data analysis’ ‘I am confident with analyzing data ’ • Teacher’s Influence (4 items); Alpha = ,851 ‘ the lecturer/tutor (combined) was excellent for the quantitative research course(s) done on the UWI campus’ ‘the teaching techniques utilized in quantitative course (s) done at UWI were not effective in advancing my understanding of quantitative research’. Proficiency with Quantitative Research (2 items); Alpha = .733 • ‘ I would rate myself as proficient at the level of quantitative research that I have studied ’ ‘my behavior to quantitative research has been positive after having done quantitative research course(s) at UWI ’. • Proficiency with Quantitative Research (1 item); GPA scores 18
Methodology cont’d Sample • The sample consisted of 91 respondents who had all completed quantitative research course(s) at the University of the West Indies, Mona campus, in Jamaica. • 59%Females & 41% Males • Faculties: – 75% Social Sciences – 9% Humanities and Education – 9% Pure and Applied Sciences – 7% Medical Science 19
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